74 resultados para hierarchical

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.

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In the scenario of social bookmarking, a user browsing the Web bookmarks web pages and assigns free-text labels (i.e., tags) to them according to their personal preferences. In this technical report, we approach one of the practical aspects when it comes to represent users' interests from their tagging activity, namely the categorization of tags into high-level categories of interest. The reason is that the representation of user profiles on the basis of the myriad of tags available on the Web is certainly unfeasible from various practical perspectives; mainly concerning the unavailability of data to reliably, accurately measure interests across such fine-grained categorisation, and, should the data be available, its overwhelming computational intractability. Motivated by this, our study presents the results of a categorization process whereby a collection of tags posted at Delicious #http://delicious.com# are classified into 200 subcategories of interest.

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In this paper we address the issue of locating hierarchical facilities in the presence of congestion. Two hierarchical models are presented, where lower level servers attend requests first, and then, some of the served customers are referred to higher level servers. In the first model, the objective is to find the minimum number of servers and theirlocations that will cover a given region with a distance or time standard. The second model is cast as a Maximal Covering Location formulation. A heuristic procedure is then presented together with computational experience. Finally, some extensions of these models that address other types of spatial configurations are offered.

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We present a simple model of communication in networks with hierarchical branching. We analyze the behavior of the model from the viewpoint of critical systems under different situations. For certain values of the parameters, a continuous phase transition between a sparse and a congested regime is observed and accurately described by an order parameter and the power spectra. At the critical point the behavior of the model is totally independent of the number of hierarchical levels. Also scaling properties are observed when the size of the system varies. The presence of noise in the communication is shown to break the transition. The analytical results are a useful guide to forecasting the main features of real networks.

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A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

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This paper is a study of the concept of priority and its use together with the notion of hierarchy in academic writing and theoretical models of translation. Hierarchies and priorities can be implicit or explicit, prescribed, suggested or described. The paper starts, chronologically, wtih Nida and Levý’s hierarchical accounts of translation and follows their legacy in scholars as different as Newmark and Gutt. The concept of priorities is hinted at also in didactic models (Nord) as well as in norm-theoretical and accounts of translation (Toury and Chesterman) within Descriptive Translation Studies. All of these authors are analyzed and commented. The paper calls for a more systematic and straightforward account of translational priorities, and proposes a few conceptual tools that stem from this research model, including the concepts of ambition and richness of a translation. Finally, the paper concludes with an adaptation of Lakoff and Johnson’s view of prototypicality and its potential usefulness in research into and the understanding of translation.

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Development of research methods requires a systematic review of their status. This study focuses on the use of Hierarchical Linear Modeling methods in psychiatric research. Evaluation includes 207 documents published until 2007, included and indexed in the ISI Web of Knowledge databases; analyses focuses on the 194 articles in the sample. Bibliometric methods are used to describe the publications patterns. Results indicate a growing interest in applying the models and an establishment of methods after 2000. Both Lotka"s and Bradford"s distributions are adjusted to the data.

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We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

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Peer-reviewed

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Herein, we have investigated the solubilization of decane into a novel nonionic gemini surfactant, myristoyl-end capped Jeffamine, synthesized from a polyoxyalkyleneamine (ED900). Starting from this system, porous silica materials have been prepared. Performing the hydrothermal treatment at low temperature, a slight increase of the mesopore diameter is observed in the presence of decane. Increasing the temperature of the hydrothermal treatment, no swelling effect of decane is detected. By contrast, the pore diameter decreases but better mesopore homogeneity and a larger wall thickness are obtained. At high decane concentration the new myristoyl-end capped Jeffamine/decane/water system forms oil-in-water emulsions, which are used as template for the formation of hierarchical porous silica materials.

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In this paper, a theoretical framework for analyzing the selection of governance structures for implementing collaboration agreements between firms and Technological Centers is presented and empirically discussed. This framework includes Transaction Costs and Property Rights’ theoretical assumptions, though complemented with several proposals coming from the Transactional Value Theory. This last theory is used for adding some dynamism in the governance structure selection. As empirical evidence of this theoretical explanation, we analyse four real experiences of collaboration between firms and one Technological Center. These experiences are aimed to represent the typology of relationships which Technological Centers usually face. Among others, a key interesting result is obtained: R&D collaboration activities do not need to always be organized through hierarchical solutions. In those cases where future expected benefits and/or reputation issues could play an important role, the traditional more static theories could not fully explain the selected governance structure for managing the R&D relationship. As a consequence, these results justify further research about the adequacy of the theoretical framework presented in this paper in other contexts, for example, R&D collaborations between firms and/or between Universities or Public Research Centers and firms.

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This paper investigates the selection of governance forms in interfirm collaborations taking into account the predictions from transaction costs and property rights theories. Transaction costs arguments are often used to justify the introduction of hierarchical controls in collaborations, but the ownership dimension of going from “contracts” to “hierarchies” has been ignored in the past and with it the so called “costs of ownership”. The theoretical results, tested with a sample of collaborations in which participate Spanish firms, indicate that the cost of ownership may offset the benefits of hierarchical controls and therefore limit their diffusion. Evidence is also reported of possible complementarities between reputation effects and forms of ownership that go together with hierarchical controls (i.e. joint ventures), in contrast with the generally assumed substitutability between the two.

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This paper presents an application of the Multiple-Scale Integrated Assessment of Societal Metabolism to the recent economic history of Ecuador and Spain. Understanding the relationship between the Gross Domestic Product (GDP) and the throughput of matter and energy over time in modern societies is crucial for understanding the sustainability predicament as it is linked to economic growth. When considering the dynamics of economic development, Spain was able to take a different path than Ecuador thanks to the different characteristics of its energy budget and other key variables. This and other changes are described using economic and biophysical variables (both extensive and intensive referring to different hierarchical levels). The representation of these parallel changes (on different levels and describable only using different variables) can be kept in coherence by adopting the frame provided by MSIASM.